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Running head: ROSTRAL ANTERIOR CINGULATE CONNECTIVITY1

Differential Functional Connectivity of Rostral Anterior Cingulate Cortex during Emotional

Interference

Akos Szekely

Stony Brook University

Rebecca L. Silton

Loyola University

Wendy Heller

University of Illinois at Urbana–Champaign

Gregory A. Miller

University of Illinois at Urbana–Champaign and University of California at Los Angeles

Aprajita Mohanty

Stony Brook University

Author Note

Akos Szekely, Department of Psychology, Stony Brook University;

Rebecca L. Silton, Department of Psychology, Loyola University;

Wendy Heller, Department of Psychology, University of Illinois at Urbana–Champaign;

Gregory A. Miller, Department of Psychology, University of Illinois at Urbana–

Champaign and Department of Psychology and Department of Psychiatry and Biobehavioral

Sciences, University of California at Los Angeles;

Aprajita Mohanty, Department of Psychology, Stony Brook University.

This research was supported by the National Institute of Drug Abuse (R21 DA14111), the

National Institute of Mental Health (R01 MH61358, P50 MH079485, T32 MH14257, T32

MH19554), and the University of Illinois Beckman Institute and Intercampus Research Initiative

ROSTRAL ANTERIOR CINGULATE CONNECTIVITY2

in Biotechnology. The authors thank Nancy Dodge, Mike Niznikiewicz, Allie Letkiewicz, Sarah

Sass, Brad Sutton, Holly Tracy, Andrew Webb, and Tracey Wszalek for their contributions to

this project

Correspondence should be addressed to Aprajita Mohanty, Department of Psychology,

Stony Brook University, Stony Brook, NY 11794-2500. Telephone: 1-631-632-7872. Email:

[email protected]

Number of words in Manuscript: 6184

mailto:[email protected]


Abstract

The rostral-ventral subdivision of the anterior cingulate cortex (rACC) plays a key role in the

regulation of emotional processing. Although rACC has strong anatomical connections with

anterior insular cortex (AIC), amygdala, prefrontal cortex and striatal brain regions, it is unclear

whether functional connectivity of rACC with these regions changes when regulating emotional

processing. Furthermore, it is not known whether this connectivity changes with deficits in

emotion regulation seen in different kinds of anxiety and depression. To address these questions

regarding rACC functional connectivity, nonpatients high in self-reported anxious apprehension

(AP), anxious arousal (AR), anhedonic depression (AD), or none (CON) indicated the ink color

of pleasant, neutral, and unpleasant words during fMRI. While ignoring task-irrelevant

unpleasant words, AD and CON showed an increase in functional connectivity of rACC with

AIC, putamen, caudate, and ventral pallidum. There was a decrease in this connectivity in AP

and AR, with AP showing greater reduction than AR. These findings provide support for the

role of rACC in integrating interoceptive, emotional, and cognitive functions via interactions

with insula and striatal regions during effective emotion regulation in healthy individuals and a

failure of this integration that may be specific to anxiety, particularly AP.


Differential Functional Connectivity of Rostral Anterior Cingulate Cortex during Emotional

Interference

The ability to actively detect sources of potential threat or reward is critical for adaptive

interactions with the environment. However, when emotional stimuli are not task-relevant, it

may be adaptive to down-regulate their processing and remain task-focused. The pregenual

portion of rostral anterior cingulate cortex (rACC), corresponding to Brodmann's 'precingulate';

architectonic areas 24, 32, and 33, has been shown to play a key role in the regulation of

emotional processing. Human neuroimaging studies show that rACC is more active when

participants are asked to regulate conflicting emotional information (Egner, Etkin, Gale, &

Hirsch, 2008; Etkin, Egner, Peraza, Kandel, & Hirsch, 2006), avoid attending to irrelevant

emotional information (Bishop, Duncan, Brett, & Lawrence, 2004; Mohanty et al., 2007;

Vuilleumier, Armony, Driver, & Dolan, 2001; Whalen et al., 1998), or exercise top-down control

upon processing of emotional stimuli (Banks, Eddy, Angstadt, Nathan, & Phan, 2007; Ochsner &

Gross, 2005; Ochsner et al., 2004; Petrovic et al., 2005). In non-clinical populations high in

anxiety (Bishop, 2009; Engels et al., 2007) and individuals diagnosed with anxiety disorders

(Klumpp et al., 2013; Shin et al., 2001; Wheaton, Fitzgerald, Phan, & Klumpp, 2014) rACC has

been shown to be less active when attempting to ignore emotional stimuli in the context of a

cognitive task but more active in individuals with depression (Elliott, Rubinsztein, Sahakian, &

Dolan, 2002; Eugène, Joormann, Cooney, Atlas, & Gotlib, 2010; Mitterschiffthaler et al., 2008).

Remaining task-focused in the presence of emotional distractors involves accurate

assessment of emotional information, resolution of interference from emotional information, and

recruitment of appropriate cognitive and motor control, a series of functions that require active

communication between limbic, striatal, prefrontal, and sensorimotor regions (Bush, Luu, &


Posner, 2000; Heatherton & Wagner, 2011; Pollatos, Gramann, & Schandry, 2007). An

examination of rACC functional connectivity with limbic, striatal prefrontal, and motor cortices

can thus clarify how rACC contributes to the integration of emotional, cognitive, and behavioral

processes. This integration may play a critical role not only in normal emotion regulation but

also in emotion dysregulation in anxiety. Tracer and cytoarchitectural studies show that rACC

has rich anatomical connections with limbic regions involved in emotional processing,

particularly anterior insular cortex (AIC) and amygdala(Mesulam & Mufson, 1982; Vogt &

Pandya, 1987; Carmichael & Price, 1995; Palomero-Gallagher, Mohlberg, Zilles, & Vogt, 2008;

Palomero-Gallagher, Vogt, Schleicher, Mayberg, & Zilles, 2009). The rostral and ventral

portions of ACC also have been shown to have anatomical connections with prefrontal and

striatal regions involved in cognitive and motor control, including lateral prefrontal and medial

orbitofrontal cortex (OFC; Carmichael & Price, 1996; Pandya, Van Hoesen, & Mesulam, 1981),

as well as brainstem motor nuclei such as periaqueductal grey (Hardy & Leichnetz, 1981;

Müller-Preuss & Jürgens, 1976), and striatum, especially ventral striatum (Devinsky, Morrell, &

Vogt, 1995; Haber et al., 2006; Kunishio & Haber, 1994). However, there are regional

variations in connectivity of rACC subregions (Morecraft, Geula, & Mesulam, 1992). For

instance pregenual portions of rACC, corresponding primarily to BA 32, shows stronger

connectivity with midcingulate, medial OFC, and frontopolar regions (Van Hoesen et al. 1993;

Carmichael and Price 1995a, 1995b; Carmichael & Price, 1996). The subgenual portion of

rACC, corresponding primarily to BA 25, shows denser anatomical connectivity with

amygdala/hippocampus, hypothalamus, periaqueductal grey, and nucleus accumbens (Devinsky,

Morrell, & Vogt, 1995; Freedman, Insel, & Smith, 2000; Ghashghaei & Barbas, 2002; Haber,

Kim, Mailly, & Calzavara, 2006; Johansen-Berg et al., 2008; Klein et al., 2007).


Although the complex anatomical connectivity of rACC makes it an ideal candidate for

active communication with limbic regions involved in emotional evaluation and frontostriatal

regions involved in cognitive and motor control, its task-related functional connectivity during

regulation of emotional interference is not well understood. It would be particularly valuable to

identify the role of this connectivity in emotion dysregulation, such as anxiety and depression.

Anxiety is characterized by an attentional bias towards threatening stimuli (Compton, Heller,

Banich, Palmieri, & Miller, 2000; McNally, 1998; Nitschke & Heller, 2002) and reduced

recruitment of rACC during attentional and cognitive control in the presence of emotional

distractors (Bishop, Duncan, Brett, & Lawrence, 2004; Etkin et al., 2006; Klumpp, Angstadt, &

Phan, 2012). However, anxiety is not a monolithic construct; different neural mechanisms are

involved in anxious apprehension (AP), characterized by verbal rumination and worry (Barlow,

1991; Heller, Nitschke, Etienne, & Miller, 1997; Sharp, Miller, & Heller, 2015), and anxious

arousal (AR), characterized by physiological hyperarousal and tension (Nitschke, Heller,

Palmieri, & Miller, 1999). Although no study to our knowledge has directly compared rACC-

functional connectivity in pure anxious apprehension vs anxious arousal groups, prior studies

show that there is lower rACC-limbic structural and functional connectivity in generalized

anxiety disorder (Etkin et al., 2010; Tromp et al., 2012), and the pattern of rACC-amygdala

responsivity predicts treatment response in GAD (Whalen et al., 2008; Holzel et al., 2013). Since

both AP and GAD are characterized by worry, we expected that functional connectvity of rACC

during emotional regulation may differ not only for anxious vs. non-anxious groups but for AP

vs. AR groups.

Anxiety and depression frequently co-occur, but attentional biases towards unpleasant

information tend to be specific to anxiety (Bar-Haim, Lamy, Pergamin, Bakermans-Kranenburg,


& Van Ijzendoorn, 2007; Mogg, Bradley, & Williams, 1995; Mogg, Bradley, Williams, &

Mathews, 1993). A few studies show increased recruitment of rACC during attentional control

in the presence of emotional distractors in depression (Elliott et al., 2002; Eugène et al., 2010;

Mitterschiffthaler et al., 2008). However, these studies did not carefully assess comorbid anxiety

or directly compare groups that isolate the specific effects of anxiety and depression (e.g., that

are carefully selected to have high depression and low anxiety scores or high anxiety and low

depression scores). This is particularly important because studies show that the degree, severity,

and type of co-occurring anxiety may differentially affect patterns of brain activation in

depression (Elliott, Rubinsztein, Sahakian, & Dolan, 2002; George et al., 1997; Herrington et al.,

2010; Mitterschiffthaler et al., 2008; Engels et al., 2010). Overall, due to the high comorbidity of

anxiety and depression as well as the dearth of studies examining different subtypes of anxiety, it

remains unclear whether psychological and neural correlates of emotional interference are

specific to certain subtypes of anxiety or depression. Although not representative of clinical

samples, pure groups that are high only in one type of anxiety or depression overcome the

problems of comorbidity seen in clinical samples and allow a careful examination of

psychological of neural dysfunction specific to particular constructs of anxiety and depression, as

championed by the National Institute of Mental Health (NIMH) Research Domain Criteria

(RDoC) initiative (Kozak & Cuthbert, 2015; Miller, Rockstroh, Hamilton, & Yee, 2016; Sharp,

Miller, & Heller, 2015; Yee, Javitt, & Miller, 2015).

In the present study, functional magnetic resonance imaging (fMRI) data were recorded

while nonpatient groups differing in trait anxious apprehension (AP), anxious arousal (AR),

anhedonic depression (AD), or none (CON) performed a task requiring them to ignore task-

irrelevant pleasant, neutral, or unpleasant distractors. We then used psychophysiological


interaction (PPI) analysis (Friston et al., 1997) to examine group differences in rACC

connectivity with 1) AIC and amygdala involved in interoceptive and emotional evaluation and

2) frontal and striatal regions involved in cognitive and motor control for unpleasant or pleasant

vs. neutral condition. Behaviorally, it was hypothesized that individuals reporting higher

anxiety would show larger interference effects due to unpleasant words than would a comparison

group, specifically AP > AR > AD = CON. This pattern was expected because attentional biases

to unpleasant stimuli are typically seen in anxiety but not depression (Gotlib & Joormann, 2010)

and because worry, a characteristic of AP, impairs processing efficiency via distraction and/or

impaired inhibition (Eysenck et al., 2007; Levin, Heller, Mohanty, Herrington, & Miller, 2007).

Neurally, it was hypothesized that functional coupling of rACC with AIC and amygdala

for unpleasant vs. neutral words would be AP < AR < AD = CON. This is based on evidence of

1) greater rACC-AIC resting-state functional connectivity (Deen, Pitskel, & Pelphrey, 2011;

Margulies et al., 2007; Seeley et al., 2007; Taylor, Seminowicz, & Davis, 2009), task-based co-

activation (Gu, Hof, Friston, & Fan, 2013; Medford & Critchley, 2010), and rACC-amygdala

task-based functional connectivity during successful resolution of emotional interference (Etkin

et al., 2006) in non-anxious individuals and 2) reduced rACC-amygdala functional connectivity

in generalized anxiety disorder (Etkin, Prater, Schatzberg, Menon, & Greicius, 2009). Next, it

was hypothesized that functional coupling of rACC with prefrontal and striatal regions for

unpleasant vs. neutral words would be AP < AR < AD = CON. This is due to evidence of 1)

greater rACC-prefrontal cortex (PFC) resting-state and task-based functional connectivity in

non-anxious individuals (Kerns et al., 2004; Mayer, Mannell, Ling, Gasparovic, & Yeo, 2011),

2) greater rACC-striatal task-based co-activation (Postuma & Dagher, 2006) with frontostrial

connectivity predicting individual differences in recruitment of cognitive control in non-anxious


individuals (Liston et al., 2006; Shannon, Sauder, Beauchaine, & Gatzke-Kopp, 2009), and 3)

greater association of AP with impairments in error monitoring (Moser, Moran, Schroder,

Donnellan, & Yeung, 2013) and reduction in frontocingulate recruitment (Silton et al., 2011).

Methods

Participants

Sixty (27 female) paid volunteers (mean age = 19.44 years, SD = 4.06) were recruited

based on questionnaire screening of 1099 college students. Participants completed the Penn

State Worry Questionnaire (PSWQ; Meyer, Miller, Metzger, & Borkovec, 1990; Molina &

Borkovec, 1994), which measures AP, and the Mood and Anxiety Symptom Questionnaire

(MASQ; (Watson, Clark, et al., 1995; Watson, Weber, et al., 1995), which measures AR with the

MASQ-AA subscale and AD with the MASQ- Anhedonic Depression (AD) subscale. The

present study used an eight-item subscale of the MASQ-AD scale that has been shown to reflect

depressed mood (Nitschke, Heller, Imig, McDonald, & Miller, 2001). Based on their responses

to these scales, participants were classified as high AP (N = 15), high AR (N = 14), high AD (N

= 9), or CON (N = 22). The AP group scored below the 50th percentile on the MASQ-AA (M =

20.33, SD = 1.97) and AD (M = 13.22, SD = 2.57) scales and above the 80th percentile on the

PSWQ (M = 68.83, SD = 3.41). The AR group scored below the 50th percentile on the PSWQ (M

= 39.09, SD = 7.54) and MASQ-AD (M = 15.36, SD = 1.29) scale and above the 80th percentile

on the MASQ-AA (M = 37.36, SD = 4.32) scale. The AD group scored below the 50th percentile

on the MASQ-AA (M = 21.22, SD = 2.86) scale and PSWQ (M = 33.11, SD = 10.19), and above

the 80th percentile MASQ-AD (M = 18.56, SD = 3.17) scale. The CON group scored below the

50th percentile on MASQ-AD (M = 12.39, SD = 2.52), MASQ-AA (M = 20.33, SD = 1.85), and

PSWQ (M = 36.50, SD = 8.62). Percentile scores were based on the initial screening samples


used in the present study (see Supplementary Materials). Correlations between MASQ-AA and

MASQ-AD, r = 0.21, MASQ-AA and PSWQ, r = -0.21, as well as MASQ-AD and PSWQ, r = -

0.22, were not significant in the sample, (all p > 0.05).

A histogram of each scale obtained from 5095 participants along with cut-offs confirmed

the generalizability of present scores (see Supplementary Materials). Specifically, scores are

consistent with scores reported in other studies conducted using USA samples. For example, in

one study that used the same percentile cut-offs (Larson et al. 2007), the mean MASQ-AA score

in the AP group was M= 22.21, SD = 3.36, in the AD group M = 22.79, SD = 4.64, and in the

CON group M = 21.31, SD = 3.96. These are very similar to the MASQ-AA scores for present

sample. Another lab using similar methods reported a MASQ-AA mean of M = 23.90, SD =

6.13, in an unselected sample (Moser et al., 2011). This mean is also very similar to the present

means reported and reflected in our larger sample (see Supplementary Materials). Although

present scores are higher than those of Schulte-van Maaren et al. (2012), this likely reflects a

fundamental difference in the sample populations (American vs. Dutch), because studies indeed

show lower prevalence of anxiety symptoms in the Netherlands (Kessler et al., 2007; Bijl et al.,

2003). Furthermore, the consistency among scores of the studies described above strongly

suggests that our scores are generalizable, at least to an American population.

The PSWQ, MASQ-AA, and the MASQ-AD were administered again when the

participants visited for the imaging session. The groups maintained their significant differences

on all three scales. The groups did not differ in age, F (3, 60) = 0.50, p = 0.61, or gender, χ2 (3,

N = 60) = 5.15, p = 0.16. Participants were right-handed, native speakers of English with self-

reported normal color vision. All participants were given a tour of the laboratory, had the study

procedures explained to them, and were screened for any contraindications for MRI


participation. Six participants (2 AP, 1 AR, and 3 CON) were excluded from fMRI data analyses

due to scanner artifacts, leaving a total of 54 participants. Subsets of the present participant

group have been used for previous publications focusing on task-related activation differences

(Engels et al., 2007; Mohanty et al., 2007); however, the analyses and questions asked in the

present research are novel and have not previously been reported.

Stimuli and Experimental Design

In line with methods reported earlier (Engels et al., 2007; Mohanty et al., 2007), the

stimuli consisted of 256 words selected from the Affective Norms for English Words set

(ANEW: Bradley & Lang, 1998). Sixty-four pleasant (e.g., birthday, ecstasy, laughter), two sets

of 64 neutral (e.g., hydrant, moment, carpet), and 64 unpleasant (e.g., suicide, war, victim) words

were carefully selected on the basis of established norms for arousal, valence , and frequency of

usage in the English language (Bradley & Lang, 1998; Toglia & Battig, 1978) as well as the

number of letters. The pleasant and unpleasant words were higher in arousal with differing

valences, whereas the neutral words were low in arousal and valence. All words ranged from

three to eight letters long. Each trial consisted of a word presented in capital letters on a black

background for 1500 ms, Tahoma 72-point font, in one of four ink colors (red, yellow, green,

blue), followed by a fixation cross presented randomly varying from 275 to 725 ms. Participants

were instructed to press one of four buttons (two per hand) to indicate the color of the word on

the screen as quickly and accurately as possible while ignoring the meaning of the word (Figure

1).

Trials were presented in blocks of pleasant, neutral, or unpleasant words. Participants

received 256 trials over the course of 16 blocks (4 pleasant, 8 neutral, 4 unpleasant) of 16 trials.

Trials were blocked because pilot studies for the current project as well as published studies

showed that a blocked design is more effective in eliciting interference due to emotional words


than is an intermixed design (Compton, Heller, Banich, Palmieri, & Miller, 2000; Dalgleish,

1995; Engels et al., 2007; Holle, Neely, & Heimberg, 1997). Furthermore, pilot studies showed

that in a block design there is an influence of emotional word blocks on the reaction time of

immediately subsequent neutral word blocks (Engels et al., 2007). Hence, order of presentation

of blocks was counterbalanced across participants to ensure that the emotional and neutral blocks

preceded each other equally often.

After every fourth block, participants were given a brief rest period. In addition to the 16

word blocks, four fixation blocks were included, with one at the beginning, one at the end, and

two in the middle of the experiment. For fixation blocks, in place of a word a brighter fixation

cross was presented for 1500 ms, followed by the standard fixation cross. To control for

stimulus familiarity, no word was repeated throughout the experiment (although some

participants saw some of the same words in a parallel EEG session on a different day). During

the course of a block, each color appeared only four times, and trials were pseudorandomized so

that a color could occur consecutively no more than twice. STIM software was used to control

word presentation and reaction-time measurement (James Long Company, Caroga Lake, NY).

MRI-compatible LCD goggles were used to display stimuli (Magnetic Resonance Technologies,

Willoughby, OH). Since pleasant stimuli are often less potent distractors than unpleasant stimuli

(Hansen & Hansen, 1988), and because attentional biases in anxiety are typically seen for

unpleasant stimuli (Bradley, Mogg, Falla, & Hamilton, 1998; Bradley, Mogg, White, Groom, &

Bono, 1999; Fox, Russo, & Dutton, 2002), present hypotheses focus on attention in the presence

of unpleasant and neutral word conditions. However, data from pleasant and unpleasant word

conditions were analyzed to confirm that hypothesized differences are seen for the unpleasant

but not the pleasant word condition.


Image Acquisition

Structural and functional MRI data were acquired using a 3T Siemens Allegra.

Functional volumes (N = 373) were acquired parallel to the axial plane of the anterior and

posterior commissure with an interleaved echoplanar imaging (EPI) sequence using the

following parameters: 2000 ms repetition time (TR), 25 ms echo time (TE), 20 slices, 7 mm slice

thickness, 3.75 mm X 3.75 mm in-plane resolution, 240 mm field of view (FOV), 60°flip angle.

Although 7mm is a relatively large slice thickness it has successfully been used to detect activity

in limbic regions related to emotional processing (Shin et al., 2005; Stein, Goldin, Sareen,

Zorrilla, & Brown, 2002). Structural images were acquired via a sagittal magnetization prepared

rapid gradient echo (MPRAGE) sequence, TR 2000 ms, TE 25 ms, 60° flip angle, 240 mm FOV,

1.3 mm slice thickness, 1 mm X 1 mm in-plane resolution.

fMRI Data Preprocessing

The first 6 volumes were discarded in order to allow the signal to reach a steady state.

The fMRI data were then preprocessed using SPM8 software (available at:

http://www.fil.ion.ucl.ac.uk/spm) implemented in MATLAB (Mathworks, Inc, Natick,

Massachusetts). Images were spatially realigned to correct for motion with a 4th-degree B-spline,

coregistered to the participant’s mean functional image and high-resolution anatomical T1 scan,

spatially normalized to a canonical T1 image, and smoothed with an 8 mm full-width half-

maximum Gaussian kernel. No participants exhibited head motion of more than 3 mm in any

direction. To test if there were differences between participant groups due to different patterns

of movement, a one-way analysis of variance (ANOVA) was performed on average movement in

each of the x, y, and z dimensions, as well as for pitch, roll, and yaw. None of the ANOVAs

yielded significant group differences in any dimension, all F values < 2.8, all p values > 0.05.

http://www.fil.ion.ucl.ac.uk/spm


Functional connectivity analyses

Given that rACC plays a crucial role in regulating task-irrelevant emotional interference,

the present study examined its functional connectivity during pleasant, neutral, or unpleasant

distractors. A PPI analysis (Friston et al., 1997; Gitelman et al., 2003; McLaren et al., 2012) was

conducted to examine how the difference between task conditions (pleasant, neutral, or

unpleasant distractors) changes the relationship of rACC with each voxel in the whole brain. PPI

analyses estimate the contribution of an interaction between a psychological factor (change in

experimental condition) and a physiological factor (activity in the seed region) to the activity in

each voxel in the brain. This basic analysis method is extended to the generalized form of

context-dependent psychophysiological interaction analyses (gPPI; http://brainmap.wisc.edu/

PPI; McLaren et al. 2008), which enables modeling of connectivity differences by group and

condition, thus increasing flexibility of statistical modeling over standard PPI methods.

Statistical testing of gPPI comparing it to standard PPI methods found that gPPI improved model

fit and sensitivity to true positive findings (Cisler et al. 2013; McLaren et al. 2012).

The rACC seed region for connectivity analyses was identified functionally as the region

that was most responsive to unpleasant vs. neutral words in the CON group (Figure 2; see

Supplementary Materials). Furthermore, across a range of fMRI studies a similar region of the

rACC emerged as sensitive to emotion-related interference or conflict (Egner, Etkin, Gale, &

Hirsch, 2008; Etkin, Egner, Peraza, Kandel, & Hirsch, 2006; Bishop, Duncan, Brett, &

Lawrence, 2004; Mohanty et al., 2007; Vuilleumier, Armony, Driver, & Dolan, 2001; Whalen et

al., 1998). Additionally, we also confirmed our results using a purely anatomically defined

rACC seed region. The anatomical rACC seed region was defined based on a meta-analysis

across nearly 10,000 studies to comprehensively map psychological states to discrete sub-regions


in medial frontal cortex using relatively unbiased, data-driven methods (De La Vega, Chang,

Banich, Wager, & Yarkoni, 2016). This approach revealed three distinct zones that differed

substantially in function, each of which was further subdivided into 2-4 smaller subregions that

showed additional functional variation. The region corresponding to rACC was selected as the

seed region that was identified as mapping onto emotional function. This anatomical seed region

corresponded primarily to BA 32 and also included some parts of BA 24.

Psychophysiological Interaction Analyses

For each subject, the ‘psychological’ term was computed by convolving the condition

onset times for pleasant, neutral, and unpleasant conditions separately with the canonical HRF,

and the ‘physiological’ term was estimated as the first eigenvariate time series of the BOLD

signal extracted from rACC seed region (described above). This represents the average BOLD

signal weighted by the voxel significance. To compute the ‘psychophysiological’ interaction

term, time series was first de-convolved with the hemodynamic signal (Gitelman et al., 2003) to

model out the effects of the canonical hemodynamic response function (HRF). The deconvolved

physiological factor was multiplied by the psychological variable and again re-convolved with

the HRF, giving the interaction term. PPI analyses were conducted by regressing activity in each

voxel against the interaction term while controlling for variance associated with the

psychological and physiological main effects. This generated the per-voxel parameter estimate

(β) maps representing the magnitude of functional connectivity between the rACC seed region

and voxel-wise activation in the brain as a function of unpleasant vs. neutral and pleasant vs.

neutral word condition.

To assess how groups differed in rACC functional connectivity as a function of

unpleasant vs. neutral words, the PPI interaction term β maps for the unpleasant vs. neutral word


contrast were subjected to a one-way ANOVA with groups (AP, AR, AD, CON) as a factor,

implemented in SPM8 (Penny et al., 2002). Similar analyses were conducted using pleasant vs.

neutral contrasts. For the hypothesis-driven examination of rACC connectivity with AIC and

amygdala, an ROI was created by drawing a 12 mm sphere in bilateral AIC (± 32, 10, -6) whose

location was obtained from an in-depth examination of insular connectivity through cluster

analysis (Deen, Pitskel, & Pelphrey, 2011) and an 8 mm sphere in bilateral amygdala (left: -21, -

5, -16; right: 22, -4, -15) whose location was obtained from a broad meta-analysis of amygdala

functional connectivity during emotional tasks (Sergerie, Chochol, & Armony, 2008) and

combining them into a single ROI mask using WFU PickAtlas (Maldjian, Laurienti, & Burdette,

2004; Maldjian, Laurienti, Kraft, & Burdette, 2003). The 3dClustSim program (December 2015

version) was used to control multiple voxelwise statistical testing in the ROI mask (Forman et

al., 1995; Cox, 1996). A corrected significance level of p < 0.05 was achieved with a minimum

cluster-size threshold of 32 contiguously activated voxels derived via Monte Carlo simulations.

For all other results, a gray-matter mask taken from WFU PickAtlas was used, with a minimum

size of 66 voxels derived via Monte Carlo simulations, resulting in a corrected threshold of p <

0.05. Next, orthogonal planned contrasts comparing experimental groups (AP and AR vs. CON

and AD, AP vs. AR, and AD vs. CON) were conducted in regions determined to be significant in

the group-wise ANOVA. Results were examined at a-corrected threshold of p < 0.05. Finally,

the MarsBaR toolbox (MARSeille Boîte À Région d’Intérêt; http://marsbar.sourceforge.net/) was

used to extract beta values from significant clusters of activation for display purposes only.

Results

Behavioral Data

http://marsbar.sourceforge.net/


All participants demonstrated greater than 80% accuracy on the task. The interference

effect due to unpleasant words was calculated as the difference in reaction time (RT) for

unpleasant minus neutral words. Across all subjects, there was a significant interference effect

due to unpleasant words, t (53) = 3.06, p = .003, and pleasant words, t(53) = 2.68, p = 0.01,

indicating that task-relevant processing of color is impaired in the presence of pleasant and

unpleasant distractors. Figure 1 shows that the unpleasant word-related interference effect was

AP>AR>CON>AD. A one-way between-groups ANOVA comparing the interference effect due

to unpleasant words for the 4 groups was marginally significant, F(3, 51) = 2.541, p = 0.07.

Dissecting this with orthogonal planned comparisons showed an interference effect due to

unpleasant words that was greater for AP and AR vs. AD and CON, t(51) = 2.18, p = 0.03, not

different for AP vs. AR, t(51) = -0.96, p = 0.34, and marginally less for AD vs. CON, t(51) = -

1.78, p = 0.08. A one-way between-groups ANOVA confirmed that these group differences in

interference effect were not driven by group differences in RT for neutral words, F(3, 51) = 0.62,

p = 0.61. Finally, a one-way between-groups ANOVA confirmed that there was no significant

effect of group on interference due to pleasant distractors, F(3, 51) = .253, p > 0.5.

Group differences in rACC functional connectivity for unpleasant vs. neutral words

Neurally, it was hypothesized that differential functional coupling of rACC with AIC and

amygdala during unpleasant vs. neutral words would be AP < AR< AD = CON. A voxelwise

between-group ANOVA yielded group differences in rACC connectivity with AIC for

unpleasant vs. neutral words at peak MNI coordinates (-28, 6, 4, peak z-score = 3.44; Figure 3A).

Planned comparisons among the groups showed weaker rACC-AIC connectivity for AP and AR

vs. CON and AD and AP vs. AR, but no significant difference for AD vs. CON. Contrary to the


hypothesis, a voxelwise between-group ANOVA on rACC-amygdala connectivity for unpleasant

vs. neutral words showed no significant differences between groups.

Next, it was hypothesized that the differential functional coupling of rACC with

prefrontal and striatal regions for unpleasant vs. neutral words would be AP < AR < AD = CON.

Using whole-brain analyses, the differential connectivity of rACC with rostral putamen (Figure

3B) and rostral caudate (Figure 3C) showed the predicted pattern. The pattern for rACC-ventral

pallidum and thalamus (Figure 3D) was also as predicted, AP < AR < AD = CON. Significant

group-related differences in rACC connectivity were found for rostral putamen (-28, 4, 2; peak z-

score = 3.38), rostral caudate (16, -12, 26; peak z-score = 3.28), and ventral pallidum and

thalamus (18, -6, 0, peak z-score = 3.02). Planned comparisons among the groups showed

weaker rACC connectivity with rostral putamen, rostral caudate, and ventral pallidum for AP

and AR vs. CON and AD and AP vs. AR, but no significant difference for AD vs. CON. An

ANOVA on neutral trials only was conducted to confirm that they did not carry the connectivity

differences. rACC connectivity to AIC and striatal regions for neutral words did not differ for

the regions outlined above, indicating that group-related differences were driven primarily by

unpleasant distractors. Finally, in order to determine that no subject in particular drove the

results, a between-subjects ANOVA was performed removing each subject from the AD group

one at a time showed no difference in significance (all ps < 0.01).

Next, we examined hypotheses regarding differential rACC functional connectivity for

groups using an anatomically defined rACC seed (de la Vega, Chang, Banich, Wager, &

Yarkoni, 2016). Overall, results were very similar to those obtained with the functionally

defined rACC seed. A voxelwise between-group ANOVA yielded group differences in rACC

connectivity with AIC for unpleasant vs. neutral words at peak MNI coordinates (-28, 6, 4, peak


z-score = 3.57; Supplementary Figure 1A). Planned comparisons among the groups showed

weaker rACC-AIC connectivity for AP and AR vs. CON and AD, as well as AD vs. CON, but

not AR vs. AP. Next, rACC connectivity with prefrontal and striatal regions was examined.

Results for rostral caudate (22, 6, 14, peak z-score = 3.26; Supplementary Figure 1C) and

pallidum (20, -2, -2, peak z-score = 3.26; Supplementary Figure 1D) replicated analyses using

the functional defined ROI. Results for rostral putamen (-24, 8, 8, peak z-score = 3.91;

Supplementary Figure 1B) showed a between-group difference for AP and AR vs. CON and AD,

as well as AP vs. AR and a greater difference for AD vs. CON.

Group differences in rACC connectivity for pleasant vs. neutral words

Using ROI analyses, no group related differences were observed in functional coupling of

rACC with AIC and amygdala during pleasant vs. neutral words. Similarly, whole-brain

analyses yielded no group-related differences in rACC functional connectivity for pleasant vs.

neutral words.

Discussion

Remaining task-focused in the presence of salient distractors involves effective

integration of sensory, emotional, cognitive, and motor processes. The rACC is anatomically

well-situated to perform this integrative function by actively communicating with limbic,

prefrontal, and striatal regions, but its functional connectivity during tasks requiring affective and

cognitive control is not well studied. The present study explored rACC connectivity during a

task that required attention to task-relevant information in the presence of task-irrelevant

emotional distractors. Behavioral results demonstrated the effectiveness of the experimental

paradigm in eliciting interference from unpleasant words, and a trend toward the hypothesized

pattern of interference for AP > AR > AD = CON. While ignoring task-irrelevant unpleasant


information, there was greater functional coupling of rACC with AIC and striatal regions in

control participants. However, there was a reduction in this coupling during unpleasant vs.

neutral distractors in participants with different types of anxiety, more so for AP than AR.

Finally, this reduction in connectivity was not seen in AD, suggesting that this effect is specific

to anxiety. These findings were confirmed using both functionally and anatomically-defined

rACC seed regions. Our findings clarify the functional connections via which rACC integrates

emotional, cognitive, and behavioral processes in the service of effective emotional and

cognitive control, as well as the failure of this connectivity in anxiety. Furthermore, present

findings were seen only for unpleasant words; no group-related behavioral or connectivity

differences were observed for pleasant words. These results are consistent with the expectation

that unpleasant stimuli would be more distracting than pleasant stimuli and serve to capture

attention more effectively in the presence of anxiety.

Although there have been few studies examining task-based differences in functional

connectivity between the ACC and the AIC, the two regions have often been shown to be co-

activated at rest and across a range of tasks (Medford & Critchley, 2010; Palaniyappan & Liddle,

2012; Seeley et al., 2007). The AIC plays an important role in interoceptive and emotional

awareness (Craig, 2009, 2010, 2011; Gu, Hof, Friston, & Fan, 2013; Jones, Ward, & Critchley,

2010; Seth, Suzuki, & Critchley, 2011; Singer, Critchley, & Preuschoff, 2009). Interoceptive

awareness is the awareness of the physiological condition of the body (Craig, 2002, 2003), and

emotional awareness refers to the ability to identify and label internal emotional experience

(Penza-Clyve & Zeman, 2002). It has been proposed that AIC plays a critical role in

interoceptive predictive coding, i.e., the inference of emotions from the physiological condition

of the body (Seth et al., 2011; Gu et al., 2013). Since emotional awareness is an important


contributor to emotion regulation (Subic-Wrana et al., 2014), rACC-AIC connectivity may play a

significant role in emotion regulation. Interestingly, AIC and ACC are the two regions of the

human brain that contain Von Economo neurons which are recently evolved cells that may be

involved in assessment of emotional and social situations (Allman, 2005). Earlier functional

imaging studies have shown stronger resting-state connectivity between AIC and pregenual ACC

(Taylor, Seminowicz, & Davis, 2009) than between AIC and other parts of ACC. Present results

bolster these findings by showing that this connectivity varies with task and individual

differences in anxiety, with compromised connectivity when regulating emotion-related

distraction in anxiety, especially in high AP.

Contrary to hypothesis, rACC-amygdala connectivity did not vary with task or individual

differences in anxiety. The lack of rACC-amygdala connectivity differences may appear

inconsistent with reports of a negative relationship between rACC and amygdala (Etkin et al.,

2006); however, other studies involved different tasks, requiring resolution of emotional conflict.

Although there is attentional competition between the unpleasant meaning of words and the color

of words in the present stimuli, there is no direct conflict between these two dimensions (Algom,

Chajut, & Lev, 2004). The absence of direct emotion-related conflict may have contributed to

the negative finding in the present study. Further, the use of pregenual rACC as opposed to

subgenual rACC as the seed region as well as present imaging parameters were not well

optimized for precise measurements of amygdala activation or connectivity.

Since striatal regions are typically involved in reward-related processing (Phan, Wager,

Taylor, & Liberzon, 2004), it is intriguing here that task and group-related differences were

found in rACC connectivity with caudate/putamen, ventral pallidum, and thalamus. The rACC,

thalamus and striatal regions in the present study constitute parts of the corticobasal circuit


(Carmichael & Price, 1995; Haber, Kim, Mailly, & Calzavara, 2006; Haber, Kunishio,

Mizobuchi, & Lynd-Balta, 1995; Giguere & Goldman-Rakic, 1988), which along with other

circuits, plays an important role in integrating sensory input with emotional/motivational

processing to modulate learning and develop task-directed behaviors and action plans (Haber,

2011). The present study provides evidence supporting the role of rACC functional connectivity

to striatal, pallidal and thalamic regions in situations requiring cognitive and motor control

during motivationally salient distractors. These results are consistent with studies showing

resting-state connectivity (Di Martino et al., 2008) and greater task-based co-activation (Postuma

& Dagher, 2006) between vmPFC (including rACC), and the ventral striatum and pallidum.

Present results of increased rACC-striatal connectivity in CON are in line with the view that

frontostriatal circuitry plays an important role in emotional control (Marchand, 2010; Shafer et

al., 2012; Wang et al., 2008) and with studies showing that individual differences in frontostriatal

connectivity predict efficiency of cognitive control (Liston et al., 2006; Shannon, Sauder,

Beauchaine, & Gatzke-Kopp, 2009). Finally, decreased rACC-striatal functional connectivity in

anxiety is consistent with the involvement of this circuitry in anxiety disorders such as panic

disorder (Marchand et al. 2009), and social phobia (Sareen et al. 2007; van der Wee et al. 2008).

Individual differences in state and trait anxiety have been shown to bias attention toward

unpleasant stimuli and slow disengagement from unpleasant stimuli but not pleasant or neutral

stimuli (Fox, Russo, Bowles, & Dutton, 2001; Sass et al., 2010; Sharp, Miller, & Heller, 2015).

In the present study, both groups high in anxiety showed lower rACC connectivity to insula and

striatal regions than did CON. AP is characterized by worry which impairs attentional control on

other tasks with emotional distractors. According to attentional control theory, worry impairs

processing efficiency and not performance effectiveness via distraction and/or impaired


inhibition (Eysenck et al., 2007). AP is strongly associated with an aberrantly high error-related

negativity (ERN), hypothesized to reflect compensation for an initial failure of goal maintenance

as worry consumes working memory resources (Moser et al., 2013). In line with this, AP is

associated with increased activity in dorsolateral PFC (Warren et al., 2013) and dorsal aspects of

ACC (Silton et al., 2011) during interference from task-irrelevant distractors. These

frontocingulate increases are interpreted as evidence of recruitment of increased top-down

control to mitigate the distracting effect of worry. It is possible that in the present study AP

participants employed greater connectivity to compensate for effects of worry while staying task-

focused during neutral distractors but were unable to do so in the presence of unpleasant

distractors.

In studies in which participants are diagnosed using Diagnostic and Statistical Manual of

Mental Disorders criteria, it is often difficult or impossible to attribute the participants’

attentional control problems to depression, anxiety, or both, given the high comorbidity of

depression and anxiety. Although present groups are not representative of the heterogeneous

presentation typically seen in individuals with clinically diagnosed anxiety and depression, the

aim of the study was not to study clinical phenomena but to examine pure constructs such as AP,

AA, and AD and their relationship with emotional-related interferences and corresponding rACC

connectivity. To develop effective and targeted treatments for anxiety and depression, it is

important to develop clinical assessment methods with high symptom sensitivity and specificity.

The identification of how attentional impairment operates in anxiety and depression may allow

development of evidenced-based treatments involving training in attentional control methods

such as cognitive control therapy (Siegle, Ghinassi, & Thase, 2007) or mindfulness-based

cognitive behavioral therapy (Segal, Williams, & Teasdale 2002). Using a carefully selected


sample in which levels of anxiety and depression were controlled, the present study sheds light

on the specificity of attentional control impairments in the presence of emotional distractors,

suggesting that these impairments are specific to anxiety and not present in depression.

Furthermore, the scores in the present study for measures of different types of anxiety and

depression are generalizable to an American sample. Findings from this study highlight the

connectivity through which rACC plays a critical role not only in normal emotion regulation but

in emotion dysregulation in anxiety.


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Figure 1. A. Participants reported the ink-color of words presented in alternating blocks of

pleasant, neutral and unpleasant words. Only performance in unpleasant and neutral conditions

was examined in the present study. B. RT for unpleasant minus neutral words for the groups

scoring high on anxious apprehension (AP), anxious arousal (AR), anhedonic depression (AD)

and neither (CON). Error bars represent Standard Error of Mean.


Figure 2. Higher rostral anterior cingulate (rACC) activation for unpleasant vs. neutral words in

CON participants constituted the seed region for functional connectivity analyses.


Figure 3: Higher functional connectivity between rACC seed region and A) Anterior Insular

Cortex (AIC), B) Putamen, C) Rostral Caudate, and D) Pallidum and Thalamus for unpleasant

than for neutral words. Error bars represent Standard Error of Mean.

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